1. A method for preparing a porous titanium oxide which comprises:
adding a particle growth inhibitor to a hydrosol, a hydrogel or a dried product of a hydrous titanium oxide obtained by the reaction of a titanium compound as a raw material with a pH adjusting agent in an aqueous solvent and represented by the general formula TiO(2-x)(OH)2x. yH2O (wherein 0.1\u2266x<2.0 and 0.3\u2266y\u226640) so as to inhibit growth of a titanium oxide particle; and
drying and calcining a mixture obtained by adding the particle growth inhibitor to the hydrosol, the hydrogel or the dried product of the hydrous titanium oxide so as to yield a titanium oxide which has a specific surface area of 80 m2g or more, a pore volume of 0.2 mlg or more and a pore sharpness degree of 50% or more,
wherein the particle growth inhibitor is a compound yielding ions containing at least one element selected from silicon (Si), magnesium (Mg), calcium (Ca) and manganese (Mn);
wherein the particle growth inhibitor is added together with the titanium compound as a raw material to the reaction solvent during the synthesis of the hydrous titanium oxide, after the synthesis and before the dehydration of the hydrous titanium oxide or after the dehydration and before the calcination of the hydrous titanium oxide; and
wherein the particle growth inhibitor is added to the hydrous titanium oxide so that an amount of the particle growth inhibitor is in a range of 0.1-3 wt % of the titanium oxide, where the particle growth inhibitor is deemed to have a weight of an oxide of the selected element for a calculation purpose.
2. A method for preparing a porous titanium oxide as described in claim 1 wherein the hydrous titanium oxide is represented by the composition formula
TiO(2-x)(OH)2x.yH2O (wherein 0.2\u2266x<1.0 and 0.3\u2266y\u226640).
3. A method for preparing a porous titanium oxide as described in claim 1 wherein the hydrous titanium oxide is obtained by using a titanium compound as a raw material and a pH adjusting agent and performing a pH swing operation alternately plural times between the precipitating pH range and the dissolving pH range of the hydrous titanium oxide in a synthesis solvent.
4. A method for preparing a porous titanium oxide as described in claim 1 wherein the hydrous titanium oxide is synthesized by using a titanium compound as a raw material and a pH adjusting agent and performing a pH swing operation in a synthesis solvent in the non-dissolving pH range of the hydrous titanium oxide alternately plural times between the range on the low pH side (1<pH\u22664) and the pH range near the isoelectric point of the hydrous titanium oxide (5.1\u2266pH\u22667.1) or between the pH range near the isoelectric point of the hydrous titanium oxide (5.1\u2266pH\u22667.1) and the range on the high pH side (8\u2266pH\u226612).
5. A method for preparing a porous titanium oxide as described in claim 1 wherein the hydrous titanium oxide is synthesized by using a titanium compound as a raw material and a pH adjusting agent and performing a pH swing operation in a synthesis solvent in the non-dissolving pH range of the hydrous titanium oxide between the range on the low pH side (1<pH\u22664) and the range across the pH range near the isoelectric point (5.1\u2266pH\u22667.1) or between the range on the high pH side (8\u2266pH\u226612) and the range across the pH range near the isoelectric point (5.1\u2266pH\u22667.1) while allowing a sufficient aging time for growth of particles in the range near the isoelectric point (5.1\u2266pH\u22667.1).
6. A method for preparing a porous titanium oxide as described claim 1 wherein
the particle growth inhibitor is added at a pH less than the isoelectric point of the hydrous titanium oxide if the particle growth inhibitor is anionic,
the particle growth inhibitor is added at a pH more than the isoelectric point of the hydrous titanium oxide if the particle growth inhibitor is cationic, or
the particle growth inhibitor is added at a pH corresponding to the isoelectric point of the hydrous titanium oxide \xb11.0 in case the particle growth inhibitor has anionic and cationic components which are simultaneously added.
7. A method for preparing a porous titanium oxide as described in claim 1 wherein the yield titanium oxide has a specific surface area of 80 m2g or more, a pore volume of 0.2 mlg or more, a pore sharpness degree of 50%, and a purity of 97 wt %.
8. A method for preparing a porous titanium oxide as described claim 1 wherein
the hydrous titanium oxide is obtained through a neutralization followed by a step of washing, and
the particle growth inhibitor is added by washing the hydrous titanium oxide with washing water containing the particle growth inhibitor during the step of washing.
9. A method for preparing a porous titanium oxide as described in claim 8 wherein washing water to be used in the step of washing of the hydrous titanium oxide contains the particle growth inhibitor in an amount in the range of 1-100 ppm on the oxide basis of the metal contained in the particle growth inhibitor.
10. A method for preparing a porous titanium oxide as described in claim 1 wherein a compound that yields ions of elements possessing catalytic activity for hydrotreating is added to the hydrosol, the hydrogel or the dried product of a hydrous titanium oxide together with the particle growth inhibitor.
11. A method for preparing a porous titanium oxide as described in claim 10 wherein the elements possessing catalytic activity for hydrotreating are principal catalyst element molybdenum (Mo) andor tungsten (W), together with one or more promoter elements selected from cobalt (Co), nickel (Ni), phosphorus (P) and boron (B).
12. A method for preparing a porous titanium oxide as described in claim 10 wherein the hydroxyl groups of the hydrous titanium oxide are exchanged by the ions of the elements possessing catalytic activity for hydrotreating.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A computer-implemented method of processing content of a document, comprising:
accessing a set of rules that define patterns that are used to identify the content as a first type of content, each rule having segmented and un-segmented patterns that can be matched to textual content written in a segmented language and textual content written in an un-segmented language, respectively;
matching the content of the document against the patterns in each rule, regardless of whether the content of the document is written in a segmented language or in an un-segmented language, to determine whether the content in the document is the first type of content;
generating a confidence score corresponding to the determination as to whether the content of the document is the first type of content, based on whether the content of the document matched a segmented pattern or an un-segmented pattern; and
processing the content of the document based on the determination as to whether the content of the document is the first type of content and the corresponding confidence score.
2. The computer-implemented method of claim 1 wherein generating a confidence score comprises:
generating a higher confidence score if the content of the document matched a segmented pattern and generating a lower confidence score if the content of the document matched an un-segmented pattern.
3. The computer-implemented method of claim 1 wherein processing the content of the document, comprises:
if the content in the document is the first type of content with a sufficient corresponding confidence score, processing the content in the document according to a first set of processing rules; and
otherwise, processing the content of the document according to a second set of processing rules.
4. The computer-implemented method of claim 1 wherein matching comprises:
matching the content of the document against both the un-segmented patterns and the segmented patterns in each rule.
5. The computer-implemented method of claim 4 wherein each pattern includes a main match pattern and a corroborating match portion and wherein matching comprises:
matching the content of the document first against the main match portion of a given pattern;
if the content of the document matches the main matching portion of the given pattern, then matching the content of the document against the corroborating match portion; and
if the content of the document matches the corroborating match portion of the given pattern, then assigning a first confidence score to the match.
6. The computer-implemented method of claim 5 wherein the corroborating match portion of the given pattern has a plurality of corroborating patterns, and wherein matching the content of the document against the corroborating match portion comprises:
matching the content of the document against each of the plurality of corroborating match patterns; and
if the content of the document matches more than one corroborating match pattern, increasing the confidence score.
7. The computer-implemented method of claim 1 wherein each rule identifies a different kind of information that, when included in the content of the document, renders the content of the document the first type of content.
8. The computer-implemented method of claim 7 wherein each rule identifies a different kind of information that, when included in the content of the document, renders the content of the document sensitive content.
9. The computer-implemented method of claim 8 wherein processing the content of the document comprises:
applying data dissemination rules to the content of the document based on whether the content of the document is identified as sensitive content.
10. The computer-implemented method of claim 8 wherein matching comprises:
matching the content of the document against patterns in a rule that identify credit card information.
11. The computer-implemented method of claim 8 wherein matching comprises:
matching the content of the document against patterns in a rule that identify social security number information.
12. The computer-implemented method of claim 8 wherein matching comprises:
matching the content of the document against patterns in a rule that identify personal information.
13. A content processing system, comprising:
a rules data store that includes a plurality of rules, each rule corresponding to a type of information and having a set of segmented patterns and a set of un-segmented patterns;
a content determination component receiving content and matching the content against the segmented patterns and the un-segmented patterns in each rule to determine whether the content includes the type of information corresponding to each rule, the content determination component assigning a confidence level to the determination of whether the content includes the type of information corresponding to a given rule based on whether the content matched a segmented pattern or an un-segmented pattern in the given rule; and
a computer processor being a functional component of the system and being activated by the content determination component to facilitate matching and assigning a confidence level.
14. The content processing system of claim 13 and further comprising:
a content processing system processing the content based on the determination of whether the content includes the type of information corresponding to a the given rule.
15. The content processing system of claim 14 wherein the content determination component matches the content against the segmented patterns and the un-segmented patterns regardless of whether the content is written in a segmented language, an un-segmented language or both a segmented and an un-segmented language.
16. The content processing system of claim 15 wherein the content determination component assigns a higher confidence level to the determination if the content matched a segmented pattern than if the content matched an un-segmented pattern.
17. The content processing system of claim 16 wherein each pattern in a rule has a main matching portion and a corroborating matching portion and wherein the content determination component matches the content first against the main matching portion and then, if the content matched the main matching portion, against the corroborating matching portion.
18. The content processing system of claim 17 wherein the corroborating matching portion includes a plurality of matching patterns.
19. The content processing system of claim 18 wherein the content determination component assigns an increased confidence level if the content matches more than one of the plurality of matching patterns in the corroborating matching portion.
20. A computer readable storage medium having computer readable instructions which, when executed by a computer, cause the computer to perform a method, comprising:
accessing a set of rules that define patterns that are used to identify content in a document as sensitive content, each rule having segmented and un-segmented patterns that can be matched to textual content written in a segmented language and textual content written in an un-segmented language, respectively;
matching the content in the document against the patterns in each rule, regardless of whether the content of the document is written in a segmented language or in an un-segmented language, to determine whether the content in the document is sensitive content;
generating a confidence score corresponding to the determination as to whether the content in the document is sensitive content, based on whether the content of the document matched a segmented pattern or an un-segmented pattern by generating a higher confidence score if the content in the document matched a segmented pattern and generating a lower confidence score if the content in the document matched an un-segmented pattern; and
processing the content of the document based on the determination as to whether the content of the document is sensitive content and the corresponding confidence score.